Clinical Validation of an Artificial Intelligence-Based Scoring System for the Modified Rankin Scale (mRS) in Patients With Stroke
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 490
- 主要终点
- Agreement Between Artificial Intelligence (AI)-Based and Manual Modified Rankin Scale (mRS) Assessments
研究概览
简要总结
This study aims to validate the clinical performance of an artificial intelligence (AI)-based automatic scoring system for the Modified Rankin Scale (mRS). The core comparison is the consistency and accuracy between the AI-generated scores and standardized manual mRS follow-up assessments performed by trained professionals. The goal is to provide a convenient, efficient, and objective tool for stroke prognosis assessment, reduce the subjective variability of manual scoring, and optimize the stroke follow-up workflow.
详细描述
This is a prospective, multicenter, observational study designed to validate the diagnostic performance of an AI-based automated scoring system for the Modified Rankin Scale (mRS) in patients with stroke. The primary objective is to evaluate the agreement between AI-generated mRS scores and standardized manual assessments conducted by trained clinicians. Secondary endpoints include the system's sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) in classifying functional outcomes.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥ 18 years, male or female.
- •Clinically diagnosed with stroke, and confirmed by cranial CT/MRI to have stroke.
- •Clinically stable, with basic communication ability at discharge or outpatient visit. The patient or a fixed family caregiver is able to cooperate with telephone follow-up at 1 week after discharge or outpatient visit.
- •Signed informed consent by the patient or their legally authorized representative.
排除标准
- •Neurological deficits caused by non-stroke etiologies (e.g., brain tumor, traumatic brain injury, encephalitis).
- •Presence of severe disturbance of consciousness, severe cognitive impairment, psychiatric disorders, or global aphasia at discharge/outpatient visit, preventing effective communication; neither the patient nor family can cooperate with follow-up or assessment.
- •Combined with severe multi-organ failure (e.g., cardiac, hepatic, renal, respiratory), with an expected survival of less than 1 month, making completion of the 1-week follow-up impossible.
- •Long-term bedridden without a fixed caregiver, with no confirmed contact for follow-up, or refusal to participate in telephone follow-up and mRS assessment.
- •Incomplete clinical data, preventing baseline data collection.
研究组 & 干预措施
AI-first interview group
Participants first receive telephone assessment by AI, followed by telephone assessment by human assessors.
Human-first group
Participants first receive telephone assessment by human assessors, followed by telephone assessment by AI.
结局指标
主要结局
Agreement Between Artificial Intelligence (AI)-Based and Manual Modified Rankin Scale (mRS) Assessments
时间窗: 7 days post-discharge or post-outpatient visit, ± 2 days
The weighted kappa coefficient quantifies the level of agreement between the Artificial Intelligence (AI)-generated Modified Rankin Scale (mRS) scores and the standardized manual mRS assessments performed by trained clinicians
次要结局
- Agreement Between AI-based and Manual Assessments of Dichotomized Modified Rankin Scale (mRS)(7 days post-discharge or post-outpatient visit, ± 2 days)
- Bland-Altman Limits of Agreement Between AI and Manual Modified Rankin Scale (mRS) Scores(7 days post-discharge or post-outpatient visit, ± 2 days)
- Diagnostic Performance of AI-Based vs. Manual Modified Rankin Scale (mRS) Dichotomization(7 days post-discharge or post-outpatient visit, ± 2 days)
研究者
qingfeng ma
MD
Xuanwu Hospital, Beijing